PosterIQ: A Design Perspective Benchmark for Poster Understanding and Generation
We present PosterIQ, a design-driven benchmark for poster understanding and generation, annotated across composition structure, typographic hierarchy, and semantic intent. It includes 7,765 image-annotation instances and 822 generation prompts spanning real, professional, and synthetic cases. To bridge visual design cognition and generative modeling, we define tasks for layout parsing, text-image correspondence, typography/readability and font perception, design quality assessment, and controllable, composition-aware generation with metaphor. We evaluate state-of-the-art MLLMs and diffusion-based generators, finding persistent gaps in visual hierarchy, typographic semantics, saliency cont...
| Authors | Yuheng Feng, Wen Zhang, Haodong Duan et al. |
|---|---|
| Primary category | cs.CV |
| Published | 25 March 2026 |
| Last updated at source | 25 March 2026 |
Connected in the knowledge graph
- creative-graphic-design/PosterIQDataset · cited by
- ArtmeScienceLab/PosterIQDataset · cited by
Models and datasets referencing this paper
- ArtmeScienceLab/PosterIQDataset
- creative-graphic-design/PosterIQDataset
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